Transcriptomic analysis of polyaromatic hydrocarbon degradation by the halophilic fungus <i>Aspergillus sydowii</i> at hypersaline conditions
Bibliographic record
Abstract
Polycyclic aromatic hydrocarbons (PAHs) are among the most persistent xenobiotic compounds, with high toxicity effects. Mycoremediation with halophilic Aspergillus sydowii was used for their removal from a hypersaline medium (1 M NaCl). A. sydowii metabolized PAHs as sole carbon sources, resulting in the removal of up to 90% for both PAHs [benzo [a] pyrene (BaP) and phenanthrene (Phe)] after 10 days. Elimination of Phe and BaP was almost exclusively due to biotransformation and not adsorption by dead mycelium and did not correlate with the activity of lignin modifying enzymes (LME). Transcriptomes of A. sydowii grown on PAHs, or on glucose as control, both at hypersaline conditions, revealed 170 upregulated and 76 downregulated genes. Upregulated genes were related to starvation, cell wall remodelling, degradation and metabolism of xenobiotics, DNA/RNA metabolism, energy generation, signalling and general stress responses. Changes of LME expression levels were not detected, while the chloroperoxidase gene, possibly related to detoxification processes in fungi, was strongly upregulated. We propose that two parallel metabolic pathways (mitochondrial and cytosolic) are involved in degradation and detoxification of PAHs in A. sydowii resulting in intracellular oxidation of PAHs. To the best of our knowledge, this is the most comprehensive transcriptomic analysis on fungal degradation of PAHs.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".